A Modern Approach to Transition Analysis and Process Mining with Markov Models in Education DOI Creative Commons
Jouni Helske, Satu Helske, Mohammed Saqr

и другие.

Опубликована: Янв. 1, 2024

Abstract This chapter presents an introduction to Markovian modelling for the analysis of sequence data. Contrary deterministic approach seen in previous chapters, models are probabilistic models, focusing on transitions between states instead studying sequences as a whole. The provides this method and differentiates its most common variations: first-order Markov hidden mixture models. In addition thorough explanation contextualisation within existing literature, step-by-step tutorial how implement each type model using R package seqHMM. also complete guide performing stochastic process mining with well plotting, comparing clustering different

Язык: Английский

A Modern Approach to Transition Analysis and Process Mining with Markov Models in Education DOI Creative Commons
Jouni Helske, Satu Helske, Mohammed Saqr

и другие.

Опубликована: Янв. 1, 2024

Abstract This chapter presents an introduction to Markovian modelling for the analysis of sequence data. Contrary deterministic approach seen in previous chapters, models are probabilistic models, focusing on transitions between states instead studying sequences as a whole. The provides this method and differentiates its most common variations: first-order Markov hidden mixture models. In addition thorough explanation contextualisation within existing literature, step-by-step tutorial how implement each type model using R package seqHMM. also complete guide performing stochastic process mining with well plotting, comparing clustering different

Язык: Английский

Процитировано

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